About Me

Hi, I’m Santino (Huynh Nguyen Son), a dedicated Computer Science graduate passionate about building innovative tech solutions.

Who I Am

Huynh Nguyen Son

Also known as Santino – Mobile App Innovator, Full-Stack Developer & AI Specialist

Quick Facts

Education: B.S. in Computer Science, GPA 3.5
Experience: 3+ years in software development
Specialties: Mobile app development, full-stack websites, AI models

My Journey

I’m Huynh Nguyen Son, also known as Santino, a Computer Science graduate with over 3 years of experience in software development. I was born and raised in a rural village in Vietnam, surrounded by the serene beauty of nature but in a simple, rustic setting. Growing up amidst such landscapes, I developed a deep fascination for technology—a magical force that can connect people, make life more vibrant, and add colors to our everyday experiences. I am the founder and creator of Salmon Note, a smart note-taking app with AI features, available on the Google Play Store. I’m passionate about the perfection and beauty of technological products, and I’m dedicated to creating solutions that are intuitive, efficient, and visually stunning. To me every small button matters because I care about every tiny detail, so I believe a product with a poor interface, lack of user-friendliness, or subpar performance has no reason to exist. My greatest idol is Steve Jobs, whose vision for innovation and design continues to inspire me in my pursuit of excellence.

My Skills

JavaScript

TypeScript

Python

C++

Kotlin

HTML

CSS

React

Node.js

Express

Nest.js

Next.js

React Native

MongoDB

PostgreSQL

MySQL

Docker

ChatGPT

Postman

Figma

Canva

Cursor

Tailwind

Bootstrap

Kaggle

Netlify

Render

AWS

...

Experience

With over 3 years in software development, I’ve honed my skills across various domains.
Intern and later employee in the AI team at EJS 365, where I contributed to building a beauty system for aesthetic clinics—focusing on facial shape recognition, golden ratio analysis, eyebrow adjustments, and makeup enhancements.
Played a key role in developing a course-selling website for Alphabet English Center in Can Tho, Vietnam, streamlining online learning for students.
Currently working on various small-scale projects and products, continuously exploring new ideas and innovations.

Achievements

I have published two scientific research papers in the field of AI and machine learning, showcasing my dedication to advancing technology through innovative solutions.

Age Prediction from Facial Images Using Deep Learning Architecture

Hai Thanh Nguyen¹, Linh Thuy Thi Pham², Dung Thi Dang³, Son Nguyen Huynh⁴, Phu Hao Dang⁵, Quoc Thien Huynh Nguyen⁶

Journal: Applied Computer Systems
ISSN: 2255-8691 (online), 2255-8683 (print)
Published: December 2024, vol. 29, no. 2, pp. 22–29
DOI: 10.2478/acss-2024-0018
Publisher: Sciendo
License: Open access under Creative Commons Attribution License

Abstract: Predicting age and gender through images is a common computer vision problem with many practical applications. However, this problem faces many difficulties because a person’s age can be affected by genetics, living environment, diet, health, gender, and other factors. Therefore, the accuracy of the prediction model may decrease due to the enormous diversity and variability in the data. In this study, we use three models, including Unet, MobileNets, and EfficientNets, to test the performance of predicting a person’s age and gender through their photos. In addition, we also adjust the learning rate parameter to find optimal performance. The best results for gender prediction are achieved by the Unet model with the highest accuracy of 97.22 %, and the MobileNets model gives age prediction results with MAE = 2.248, learning rate 0.001 for optimal performance in the models of our study.

¹College of Information and Communication Technology, Can Tho University, Can Tho, Vietnam
^2–6Can Tho University of Technology, Can Tho, Vietnam

An Approach on Data Augmentation with One-Dimensional Convolutional Neural Network for Infant Cry Classification

Hai Thanh Nguyen^a, Linh Thuy Thi Pham^c, Huynh Nguyen Son^c, Thao Nguyen Tran^b

Published: Digital Signal Processing (DSP-D-25-00613)

Abstract: Approximately 385,000 newborns are born worldwide daily, making their medical care and monitoring a top priority. While infant cries may seem indistinguishable to many, they serve as the primary communication between infants and the world, reflecting various health conditions such as discomfort, hunger, or sleepiness. Numerous studies have been conducted to analyze and classify infant cries, aiming to develop accurate, reliable, and practical models. Given the limitations of labeled infant cry datasets, we designed and experimented with multiple data augmentation techniques to enhance model performance. Specifically, we tested 8 data augmentation methods on a One-Dimensional Convolutional Neural Network (1D-CNN) architecture, achieving varying levels of accuracy. Our results show that applying variant dataset methods 3 and 4 yielded the highest accuracy of 99.9902%. Additionally, increasing audio frequency improved classification accuracy, while higher environmental noise levels led to performance degradation.

^aCan Tho University, Can Tho, Vietnam
^bCan Tho University of Technology, Can Tho, Vietnam
^cUniversity of Bolton, Bolton, United Kingdom

Notable Projects

I’ve worked on a wide range of projects spanning websites, mobile apps, and AI models. From building intuitive mobile applications with AI-powered features to crafting robust full-stack websites, my portfolio reflects my versatility and passion for technology.

Explore My Projects

My Interests

I’m deeply passionate about advancing technologies like AI, machine learning, generative AI, LLMs, NLP, and image processing. I enjoy developing AI models and integrating them into practical applications like mobile apps and websites. Beyond tech, I love hiking, capturing artistic landscape photography, watching movies, writing movie reviews, practicing boxing, and learning languages such as English and French.

My Mission

My mission is to create impactful, user-centric solutions that drive progress and accessibility. I aim to craft useful applications that reach and benefit a wide audience, bridging the gap between technology and user needs while delivering innovative, scalable, and efficient software. I’m committed to growing as a professional in the tech industry and pushing the boundaries of what’s possible.

My Motto

I believe that creativity, unique thinking, and meticulous preparation are the key ingredients to unlocking the magic of technology. By combining innovative ideas with a solid foundation, we can create solutions that transform lives and inspire progress.